Instructions to use Startup-Exchange/tps_sentimental_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Startup-Exchange/tps_sentimental_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Startup-Exchange/tps_sentimental_analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Startup-Exchange/tps_sentimental_analysis") model = AutoModelForSequenceClassification.from_pretrained("Startup-Exchange/tps_sentimental_analysis") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Intended uses & limitations
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Sentimental Analysis
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## Training and evaluation data
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## Intended uses & limitations
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Sentimental Analysis
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| Lines | Emotions |
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|HARPER sits at a table alone in a room.| Neutral |
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|Hi, Harper. I’m really happy you came.| Positive |
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|Happy Father’s Day.| Positive |
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|It was Christmas.| Neutral |
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## Training and evaluation data
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